Water distribution extracted from mining subsidence area using
Kriging interpolation algorithm
(College of Geosicence and Surveying Engineering, China University of Mining & Technology, Beijing 100083, China)
Abstract: By comprehensively analyzing the data of geology and mining, Kriging algorithm was introduced to analyze the thematic information of geological data, to rapidly extract mining parameters for predicting mining subsidence, and to effectively integrate geomorphology and predict information. As a result, the change information of water body is successfully detected from the prediction of surface subsidence due to mining activity. Analysis shows that the elevation of farmland in the west side of water body will be lower than ever, and the west part farmland will be submerged. However, there is no evidence for impacting the villages. All the information provides a reference for efficiently assessing environmental impact due to mining activity, which can help to govern the subsidence of the area reasonably.
Key words: Kriging interpolation; water body; mining subsidence; prediction parameters; data fusion